{"uid":"cap_hyKq_dJitYTtTUmIptarL","slug":"promotion-observations-string-normalisation-secondary-measure-9c7759ba","name":"Promotion Observations — String Normalisation + Secondary-Measure Weighted Mean","description":"Promotion observations — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied promotion observations records (discount_amount, units_sold). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-retail-05-034?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","discount_amount","units_sold"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"units_sold":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"store_group":{"type":"string","default":"","maxLength":80},"discount_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","units_sold":1,"store_group":"group-a","discount_amount":10},{"date":"2026-10-02","row_id":"row-2","units_sold":2,"store_group":"group-b","discount_amount":20},{"date":"2026-10-03","row_id":"row-3","units_sold":3,"store_group":"group-a","discount_amount":15},{"date":"2026-10-04","row_id":"row-4","units_sold":4,"store_group":"group-b","discount_amount":30}],"maxItems":200,"minItems":1},"field":{"enum":["discount_amount","units_sold"],"type":"string","default":"discount_amount"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_3-vIUfwrSzMGIK7Vi_ye0","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs string normalisation and secondary-measure weighted mean analysis on up to 200 promotion observation rows covering discount_amount and units_sold fields.","exampleAgentPrompt":"Can you run string normalization and a secondary-measure weighted mean on my promotion observations? I have rows with store_group, date, discount_amount, and units_sold — please analyze the discount_amount field across up to 200 rows.","exampleUseCases":[{"title":"Retail promotion discount analysis","prompt":"I have 150 rows of promotion data with store_group names that need cleaning and I want a weighted mean on the discount_amount field — can you normalize the strings and compute the secondary-measure weighted mean for me?"},{"title":"Units sold weighted average across store groups","prompt":"Run string normalization and a secondary-measure weighted mean on my units_sold promotion observations — I've got about 80 rows with store groups like 'group-a' and 'group-b' and dates from last quarter."},{"title":"Standardizing promotion records before reporting","prompt":"Before I compile my promo report, can you normalize the store_group strings and calculate the weighted mean for discount_amount across my 60 promotion observation rows?"}],"resultDescription":"Returns two independent analytical reports: (1) string-normalised versions of the store_group and other text fields in the supplied promotion rows, and (2) a secondary-measure weighted mean computed over the selected numeric field (discount_amount or units_sold) across the supplied rows. Up to 200 rows are processed per call.","failureModes":["More than 200 rows submitted — request will be rejected with a row-limit error","Invalid date format (not YYYY-MM-DD) causes validation failure","Missing required fields (row_id, store_group, date, discount_amount, units_sold) triggers schema error","Numeric values outside the allowed range (±1,000,000,000,000) cause rejection","Invalid field selector (not 'discount_amount' or 'units_sold') causes enum validation failure","Payment not provided or insufficient USDC causes 402 response"],"whenToPreferThis":"Choose this endpoint when you need both string normalization and secondary-measure weighted mean in a single paid call on promotion observation data (discount_amount, units_sold) for up to 200 rows, without needing live data lookups, predictions, or external integrations. It is cost-efficient at $0.01 USDC for two bundled reports.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:10:23.942Z","isFirstParty":false,"canonicalSlug":"promotion-observations-string-normalisation-secondary-measure-9c7759ba"}